Frontend architecture for AI-assisted teams
Ship faster with AI without turning your frontend into technical debt.
AI helps your team write code fast. I make sure the codebase doesn't slow them down as it grows.
The problem
Your AI-generated code is getting faster. Your codebase is getting slower.
You're paying for AI tools and a growing team. So why is everything taking longer?
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Features take longer every month
Work that used to take days now takes weeks. Your team is working hard. It's just harder to get anything done.
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Your developers are deciding, not building
With no clear structure, every feature starts with the same questions: where does this go, and how should it work? That time adds up, and none of it ships anything.
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Fixes break other things
A change in one place causes a bug somewhere else. Releases get riskier, and your customers notice.
Under the hood
What your developers are dealing with
When shipping is this easy, the architecture decisions get skipped. Here's what that looks like in the code.
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Nobody agrees where code goes
Every PR invents its own pattern. Without shared rules, each developer and each AI session makes a different call.
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API calls are everywhere
Fetching and error handling are spread across dozens of components. Change one endpoint and you're hunting for every caller.
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Review is the bottleneck
PRs got bigger and harder to read. Code only ships as fast as someone can trust it.
AI made writing code cheaper. It didn't make architecture decisions cheaper.
The code usually isn't bad line by line. There's just no plan behind the next fifty changes, so everything gets a little slower and riskier to touch.
What I do
Three ways I can help
Start with the audit. It's fixed-price, and you keep the plan whether or not you hire me for the rest.
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Audit
I go through your codebase and tell you what to fix first, and what to leave alone.
- Components and state
- API and data layer
- Linting, types, tests, CI
Findings ranked P0 P1 P2
See details
What I do
- Go through every feature area, not just a sample
- Trace how data moves from your API to the screen
- Map what depends on what, and where a change ripples
- Spot the patterns your AI tools keep repeating, good and bad
- Review your tooling, tests, and CI setup
- Weigh every problem by risk and cost to fix, and decide what's actually worth fixing
What you get
- A written report. Each finding covers where it is, why it matters, and what I'd do about it.
- Findings ranked, so you know what to tackle first
- A target architecture for your app
- Effort estimates for each fix
- A call to walk through it together
- Timeline
- About one week
- I need
- Read access to the repo and 30 minutes with someone who knows the code
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Refactoring
I fix what the audit found, one agreed chunk at a time.
- Move API calls into a service layer
- Merge duplicate logic
- Organize code by feature
Scoped up front, so you know when it's done.
See details
What I do
- Plan the order of changes so nothing breaks halfway through
- Build the new pattern once, then move features onto it one by one
- Update imports, types, tests, and mocks in every file the change touches
- Run and fix the test suite after every step
- Check each feature still works the same from the user's side
- Split it into PRs small enough to actually review
What you get
- An agreed part of your app moved onto the new structure
- Working features and passing tests at every step
- Notes on what changed and why, for whoever touches it next
- A fixed scope and price, agreed before I start
- Timeline
- Quoted per chunk. Most take 1–3 weeks.
- I need
- Access to your dev environment and someone to review PRs
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Guardrails
Rules your tools enforce, so the cleanup doesn't slowly undo itself.
- Architecture docs and AI agent instructions
- Lint rules and import boundaries
- CI checks that catch drift
AI keeps writing code. It just follows your rules.
See details
What I do
- Turn your architecture into rules people and AI tools can both follow
- Set up your tooling to catch rule-breaking automatically
- Test the rules against your real code, not a template
- Tune them until they catch real problems without blocking good work
- Check your AI tools actually follow them in practice
What you get
- Architecture docs written for both your team and your AI agents
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Instruction files for the AI tools you use, like
CLAUDE.md - Automated checks in linting and CI
- A walkthrough for your team
- Timeline
- 1–2 weeks. Often done alongside refactoring.
- I need
- Access to your repo and CI settings
Why not just do this in-house?
You could. But it means pulling your developers off features for weeks, and cleanup work usually loses that fight. I come in with no competing backlog and no attachment to how the code got this way. Your team keeps shipping while I do this.
Want ongoing help? I also do monthly check-ins to catch new problems before they pile up.
What changes
An obvious place for every new change
When the structure answers "where does this go?", your team and your AI tools stop guessing.
components/
UserDashboard.jsx
UserDashboard2.jsx
UserDashboardNew.jsx
UserDashboardFinal.jsxSame logic, copied into every version.
src/
components/
features/
users/
billing/
dashboard/
services/
api/
auth/
hooks/
utils/
types/
tests/Each feature lives in one place. Data access goes through services.
Security
Your code stays with you
Nothing proprietary leaves your systems or goes into my personal accounts.
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Your environment
I work in your repo, your dev setup, and your staging.
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Your AI tools
If AI helps with the work, it runs on your accounts under your policies. No AI allowed? I can do it by hand. It just takes longer.
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Small pull requests
Your team reviews and merges everything. No surprise rewrites.
Get in touch
Not sure how bad it is? That's what the audit is for.
Tell me what you're building and what's slowing your team down. No technical details needed. I'll tell you honestly if I can help.
Or just send your app's URL. I'll point out a few things I'd look at first.